Análisis y Predicción de Series Temporales, 2025.

2025-09-17 Session

• ARMA processes, lecture notes
• Recommended reading: Same as the previous lecture, plus Ch.11 of Krispin (2019). For more mathematical background up to Ch02 of Shumway & Stoffer (2017)

2025-09-10 Session

• Lab 2 ARMA models, additional notes
• Recommended reading: Section 2.9 and Chapters 3 and 6 of fpp2. Also watch the videos in the corresponding chapters of fpp3
• Examples of MA process
• Python code

2025-09-03 Session

• Lab. 1 Decomposition, additional notes
• Recommended reading: Chapters 1 and 2 of fpp2. Also watch the videos in the corresponding chapters of fpp3
• Forecasting: Principles and Practice, the Pythonic Way
• Time-Series Forecasting: Deep Learning vs Statistics. A Medium post (2023) by N. Kafritsas.
• Python code

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Krispin, R. (2019). Hands-on time series analysis with r: Perform time series analysis and forecasting using r. Packt Publishing Ltd. Retrieved from https://github.com/PacktPublishing/Hands-On-Time-Series-Analysis-with-R

Shumway, R. H., & Stoffer, D. S. (2017). Time series analysis and its applications: With r examples. Springer International Publishing. Retrieved from https://link.springer.com/book/10.1007/978-3-319-52452-8